Multimodal sensing refers to the integration of multiple sensor types to collect various environmental data. By leveraging the strengths of different modalities, it enables more accurate and comprehensive understanding of complex scenarios. As a result, multimodal sensing is integral to mission-critical Internet-of-Things (IoT) systems such as smart cities, intelligent transportation, and defense applications. Robust cybersecurity is essential to their reliable operation, ensuring core objectives like encryption, authentication, and access control. However, while IoT systems increasingly rely on multimodal sensing, cybersecurity approaches that exploit this capability remain largely unexplored. This project addresses this gap by developing multimodal sensing-based security mechanisms to enhance the protection of mission-critical IoT systems. It also lays the foundation for broader applications of multimodal sensing in security. In parallel, the research advances scientific knowledge at the intersection of wireless networking, mobile sensing, and AI. Educational materials will be made publicly available, and the research will be integrated into curriculum development, undergraduate research, and increased participation in computing. This project pursues a challenging research agenda, termed MSS, focused on developing, prototyping, and evaluating innovative Multimodal Sensing-Based Security (MSS) mechanisms for mission-critical IoT systems with inherently heterogeneous sensi